Carbon Neuttra
New Member
I originally posted this over at **********, but figured it may be of interest here - it does have more of a firewood slant, but tree related accidents are in there...
As part of my work, I recently came across data that showed a year’s worth of data from 100 emergency rooms across the US. It contains every incident where a consumer product was involved. Chain saws, axes, and log splitters are included. I took these products, and also added any accidents where “tree” or “fire wood” appeared in the accident description. I than ran through the data pulling out any rows that didn’t belong there. Obviously, only log splitters could be considered accidents solely involved with wood burning, but all involve dealing with wood and trees.
This link will take you to the graphic (it can take a few seconds to load). The top chart shows every single incident that occurred, plotted against age, type of injury, and the bars colored by body part. If you hover your mouse over a single bar, a tooltip will pop up that contains the accident description. The filter at the top right allows you to select just accidents involving log splitters, or chainsaws, or everything. You can also highlight a body part, and it will grey out all the other body parts. If you look at the data with everything selected, you can see for example, that lacerations are the most common injury (number of bars in this column), or that amputation involves only fingers (thankfully, I suppose)
The chart on the bottom right shows the same data, but individual cases are not shown - the size of the box reflects the number of cases involving that body part/injury type.
The chart on the right shows the time of year - you can see the peak in October for log splitter injuries if you choose this on the filter.
Why did I do this? Two reasons - I like dealing with data like this.., but secondly I have found this data instructive - especially when reading some of the accident descriptions - it’s made me think more about PPE, what perhaps I shouldn’t do, what to really look out for, and so on. I hope you do too.
As part of my work, I recently came across data that showed a year’s worth of data from 100 emergency rooms across the US. It contains every incident where a consumer product was involved. Chain saws, axes, and log splitters are included. I took these products, and also added any accidents where “tree” or “fire wood” appeared in the accident description. I than ran through the data pulling out any rows that didn’t belong there. Obviously, only log splitters could be considered accidents solely involved with wood burning, but all involve dealing with wood and trees.
This link will take you to the graphic (it can take a few seconds to load). The top chart shows every single incident that occurred, plotted against age, type of injury, and the bars colored by body part. If you hover your mouse over a single bar, a tooltip will pop up that contains the accident description. The filter at the top right allows you to select just accidents involving log splitters, or chainsaws, or everything. You can also highlight a body part, and it will grey out all the other body parts. If you look at the data with everything selected, you can see for example, that lacerations are the most common injury (number of bars in this column), or that amputation involves only fingers (thankfully, I suppose)
The chart on the bottom right shows the same data, but individual cases are not shown - the size of the box reflects the number of cases involving that body part/injury type.
The chart on the right shows the time of year - you can see the peak in October for log splitter injuries if you choose this on the filter.
Why did I do this? Two reasons - I like dealing with data like this.., but secondly I have found this data instructive - especially when reading some of the accident descriptions - it’s made me think more about PPE, what perhaps I shouldn’t do, what to really look out for, and so on. I hope you do too.
